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A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment
Authors:Abderrahmane Bensmaine  Mohammed Dahane  Lyes Benyoucef
Affiliation:1. LGIPM/ENIM, 1 Route d’Ars Laquenexy, CS65820, 57078 Metz, France;2. Aix-Marseille University, LSIS UMR 7296, Faculté de Saint Jérôme, Avenue Escadrille Normandie Niemen, 13397 Marseille Cedex 20, France
Abstract:This paper deals with a problem of reconfigurable manufacturing systems (RMSs) design based on products specifications and reconfigurable machines capabilities. A reconfigurable manufacturing environment includes machines, tools, system layout, etc. Moreover, the machine can be reconfigured to meet the changing needs in terms of capacity and functionality, which means that the same machine can be modified in order to perform different tasks depending on the offered axes of motion in each configuration and the availability of tools. This problem is related to the selection of candidate reconfigurable machines among an available set, which will be then used to carry out a certain product based on the product characteristics. The selection of the machines considers two main objectives respectively the minimization of the total cost (production cost, reconfiguration cost, tool changing cost and tool using cost) and the total completion time. An adapted version of the non- dominated sorting genetic algorithm (NSGA-II) is proposed to solve the problem. To demonstrate the effectiveness of the proposed approach on RMS design problem, a numerical example is presented and the obtained results are discussed with suggested future research.
Keywords:Reconfigurable manufacturing systems  RMS design  Machines selection  Multi-objective metaheuristic  NSGA-II
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